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Hewlett Packard Enterprise

Builds servers, networking and private cloud

Principal Engineer - Storage Data Science and Analytics

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Data Science, Engineering, Mathematics, or a highly technical, data-oriented discipline.
  • At least 10 years of industry experience in software product development or enterprise data science, with emphasis on distributed systems, storage, or cloud infrastructure architectures.
  • Advanced mastery of machine learning algorithms, including time-series forecasting, clustering, anomaly detection, and random forests, and deep learning frameworks.
  • Expert-level Python or Go programming, with strong knowledge of data structures, algorithmic complexity, and multithreaded and multiprocess programming.
  • Concrete experience building and fine-tuning large language models, prompt engineering, and leveraging vector databases.
  • Experience building scalable data pipeline designs and deploying them in a multinode environment.
  • Ability to explain technical architectural trade-offs, algorithms, and AI solutions clearly to nontechnical business leaders and executive management.
  • A proven record of industry innovation demonstrated through whitepapers, industry conference contributions, or patents in software and analytical design.

Responsibilities

  • Define organization-wide data architecture strategy and analytical roadmaps for software systems across HPE's hybrid cloud platform.
  • Design, deploy, and scale machine learning and deep learning code for reliable operation in worldwide production edge-to-cloud environments.
  • Collaborate with data engineering to establish standardized ELT patterns, big data storage views, and high-throughput, low-latency streaming pipelines supporting technologies such as Kafka and Spark.
  • Integrate large language model workflows, retrieval-augmented generation, and agentic systems into storage customer support analytics and digital products to automate troubleshooting.
  • Partner with product management, storage hardware engineers, and business executives to translate business challenges into production-ready analytical solutions.
  • Provide career guidance, conduct design reviews, and mentor senior engineers and data scientists across multiple Scrum teams.

Desired Qualifications

  • Master Kubernetes or equivalent systems to manage containerized workloads dynamically.
  • Develop predictive, prescriptive, and generative AI models to map data paths, enhance memory and space management, and predict capacity or hardware failure across global enterprise clusters.
  • Validate complex, distributed telemetry data from customer storage networks to uncover structured insights that drive automated mitigation and system reliability.
  • Experience with enterprise storage and C/C++ or system internals.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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